Statistical and stochastical properties of inter spike interval time series
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1
Department of Electronics and Telecommunications, Polytechnical Engineering College Subotica, Serbia
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2
Peter Pazmany Catholic University-Semmelweis University, Hungary
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3
Inserm, U846, Stem Cell and Brain Research Institute, France
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4
Centre de Recherche Cerveau & Cognition, UMR CNRS 5549, Faculté de Médecine de Rangueil, France
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5
KFKI Research Institute for Particle and Nuclear Physics of the Hungarian Academy of Sciences, Hungary
Inter Spike Interval (ISI), which characterizes neuronal activity, exhibits large variation as shown with the coefficient of variation (CV) and the local coefficient of variations (LV) in the cerebral cortex. The variation of ISI is fundamentally influenced by the input of the neurons i.e. by network activity. To better understand neuronal behavior at the network level, it is important to determine the statistical properties of ISI. It is often assumed that ISI can be described by an appropriate probability density function (pdf) of exponential type. CV and LV are frequently used statistics to determine the probability density properties of ISI. However, these measures have many disadvantages. Neither CV, nor LV is robust when the pdf is inherently multimodal. The probability functions of CV and LV statistics are hard to determine, so the statistical validation of CV and LV results by confidence intervals is unfeasible. We used comprehensive statistical methods to analyze the ISI time series, taken from experimental recordings in different cortical areas of awake, behaving macaque monkeys. We estimate the most probable pdf function for each ISI time series. The analysis shows that most of ISI time series are statistically stationary but can not be described by exponential pdf. The two most frequently observed pdf functions are the General Extreme Value and Log-Normal. We conclude that spike time arrival does not follow a Poissonian law. The stationary property allows further stochastical analysis based on correlation functions and spectral analysis to formulate realistic statistical neuronal models.
Conference:
12th Meeting of the Hungarian Neuroscience Society, Budapest, Hungary, 22 Jan - 24 Jan, 2009.
Presentation Type:
Poster Presentation
Topic:
Research on the cerebral cortex and related structures
Citation:
Minich
J,
Negyessy
L,
Procyk
E,
Barone
P,
Odry
P and
Bazso
F
(2009). Statistical and stochastical properties of inter spike interval time series.
Front. Syst. Neurosci.
Conference Abstract:
12th Meeting of the Hungarian Neuroscience Society.
doi: 10.3389/conf.neuro.01.2009.04.213
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Received:
09 Mar 2009;
Published Online:
09 Mar 2009.
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Correspondence:
Janos Minich, Department of Electronics and Telecommunications, Polytechnical Engineering College Subotica, Subotica, Serbia, interspike@gmail.com